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REU BlogPost: 2018 Joint PI Meeting NSF Big Data and Hubs & Spokes

On June 20th 2018, our group of 12 REU Educational Data Mining research interns attended the 2018 Joint PI Meeting NSF Big Data at Westin Alexandria. According to its website, the conference is “designed to bring together key stakeholders in NSF’s Big Data programs. PIs and select representatives from government and industry will convene in Alexandria, VA to discuss current research, identify major challenges, and discuss promising directions for future studies”.

In the morning, we listened to many lightning talks by various PI’s in Big Data. They went up to the front of the stage and talked with PPT slides on the big screen. It was fascinating to listen to a lightning talk where PIs and grad students summarized their research projects in a 2-minute speech. They only talked about several important points of their research in order to peak the audience’s interest and entice them to visit them during the poster session.

After the lightning talk ended, we took a 30 minute coffee break and sat in on Susan Davidson’s Talk. Her talk focused on the idea of automatically generating data citations for data in a database. I thought it was a very well delivered speech and hope to refer back to her ideas when I need to cite my data in my future research papers.

Then, after eating lunch provided by the hotel, we walked around to different posters by NSF funded Big Data researchers from all over the country. Some of the interesting posters I found were:

Population Reproduction of Poverty at Birth from Surveys, Censuses, and Birth Registrations

Population Reproduction of Poverty at Birth from Surveys, Censuses, and Birth Registrations

Using Big Data to Investigate Longitudinal Education Outcomes through Visual Data Analytics

Using Big Data to Investigate Longitudinal Education Outcomes through Visual Data Analytics

High Dimensional Statistical Machine Learning for Spatio-Temporal Climate Data

For me, a key takeaway from this poster session was the importance of communication. As I have limited knowledge of these various machine learning concepts, I could not understand some of the posters just by looking at them. However, when a great presenter like Alex Bowers, who is the PI for the poster, “Using Big Data to Investiagate Longitudinal Education Outcomes through Visual Data Analytics”, explained his research concepts in a easy, concise, and motivating manner, I could definitely understand the poster better. I learned the significance of communicating results to an audience that has differing levels of knowledge about the topic; no matter how great the research was, if it is not presented well, it loses its ability to shine.

Attending this conference was a great learning experience for me. The lightning talks showed me various researchers explaining their work, that in some cases, lasted up to a year, in a couple of minutes. Susan Davidson’s talk reinforced in me the importance of citing data. Most importantly, the poster session was the most memorable because I learned that communicating your research in a easy, concise, and motivating way is key in “showing off” the work that many researchers have done.